AI Engineer

Adarga Ltd; City Of London; On-site; GBP 60,000 - 80,000; Full time

Job summary

A leading Defence Tech company in London is seeking an experienced AI/ML Engineer to design and develop innovative machine learning solutions for intelligence analysts. Candidates should have a Master's or PhD and 3+ years of practical experience in machine learning. Strong Python skills and familiarity with Generative AI techniques are essential. The role involves collaboration with cross-functional teams and maintaining high-performance AI systems.

Qualifications

• 3+ years experience applying machine learning in production settings.
• Experience with Generative AI techniques.
• Strong Python skills and familiarity with ML frameworks.

Responsibilities

• Design and develop machine learning models for Defence applications.
• Collaborate with product teams from concept to production.
• Maintain health and resilience of production systems.

Skills

Machine Learning

Python Development

Generative AI Techniques

Clear Communication

Collaborative Mindset

Education

Advanced degree (Master’s or PhD) in relevant field

Tools

Hugging Face

spaCy

PyTorch

Scikit-learn

Kubernetes

Job description

About Adarga

Adarga is the UK’s only sovereign Defence Tech company specialising in applied AI solutions across intelligence, operations and planning. In an era of information overload, Adarga delivers technology that enables our mission partners to act with speed, clarity and confidence.

By unlocking the value of their data, we help our partners make better decisions that achieve mission-critical outcomes.

Our team is a hybrid of domain specialists and technologists. We believe this layering of experience is key to building cutting edge AI that is operationally relevant, solving real problems, to drive real outcomes.

This is a unique time to join Adarga. With our foundations set in NLP, computational linguistics and graph technology we now draw on the latest ideas in generative AI and knowledge representation, as we set our sights firmly on defining and building the next era of sovereign AI capability for mission partners across the Defence and National Security sectors.

To work at Adarga you have to care deeply about the mission. We exist to support those with the ultimate task: upholding the liberties and values that define our society. In today’s contested, multipolar world, this cannot be taken for granted.

We want people who are comfortable with uncertainty, who want to own decisions, who want to drive a vision. If that is you, get in touch!

If you don\'t match all the skills and qualifications but care about our mission then we\'d encourage you to back yourself and apply anyway. We all learn by doing

About the role:

You will be joining our Product org, a cross functional team of software engineers, machine learning specialists, domain experts and product specialists, focussed on building a suite of capabilities for intelligence analysts working across Defence and National Security.

You will build AI products designed to move the human up the value chain thereby enabling intelligence analysts to act with speed, clarity and confidence.

We are looking for someone to leverage their expertise in AI/ML engineering to design, develop, and deploy innovative machine learning and algorithmic solutions. We want someone adept at building models that solve hard problems.

Responsibilities

• Design and develop machine learning models and algorithmic solutions that address complex, real-world challenges for users in Defence and National Security.
• Partner with product managers, product engineers, and domain experts to deliver ML-powered features from concept through to production.
• Engineer solutions with a deep understanding of algorithmic complexity and the operational cost of running models at scale.
• Communicate model choices, assumptions, and tradeoffs with clarity - whether you’re speaking to fellow engineers, product stakeholders, or end users.
• Contribute to the development of robust, user-facing AI capabilities that are both high-performing and reliable - shipped fast, and iterated with care.
• Take full ownership of your work: from early experimentation through to deployment, monitoring, and ongoing optimisation.
• Help maintain the health and resilience of our production systems, debugging distributed pipelines when things go wrong.
• Stay close to the frontier of ML and AI research, continuously exploring ways to apply emerging techniques and tools to deliver better outcomes for users.

Skills and Qualifications

• Advanced degree (Master’s or PhD) in Computer Science, Machine Learning, NLP, or a related technical field.
• 3+ years of hands-on experience applying machine learning in production settings, ideally within enterprise or mission-critical environments.
• Practical expertise with Generative AI techniques—fine-tuning and evaluating large language models (LLMs), building RAG pipelines, and experimenting with agentic AI workflows.
• Strong Python development skills and familiarity with modern ML and NLP frameworks and tooling (e.g. Hugging Face, spaCy, PyTorch, Scikit-learn).
• Familiarity with Kubernetes and infrastructure for deploying and scaling ML models is a plus.
• Exposure to systems integration challenges (e.g. connecting ML workflows with data stores like PostgreSQL or search systems like Elasticsearch) is valued.
• Clear, confident communicator who thrives in cross-functional settings and can bridge the gap between technical depth and product impact.
• A curious mindset - you stay sharp by experimenting with new tools and refining your approach based on what works.

Interview Process

• Phone Interview – Remote (30 mins)
• Technical Interview – Remote/In person (1 h)
• Final Interview – Onsite (1 h)

Successful applicants may be required to undergo national security vetting upon appointment or during employment in this role. Applicants must meet the security requirements set out by UK Security Vetting (UKSV), and understand what is required in the associated UKSV: Vetting Guidance before they can be appointed.